Modeling and control of biotechnological processes, systems biology, and synthetic biology
Mathematical models are central in systems biology and provide new ways to understand the function of biological systems, helping in the generation of novel and testable hypotheses, and supporting a rational framework for possible ways of intervention, like in e.g. genetic engineering for improved industrial biotechnological production, drug development or treatment of diseases. Since the amount and quality of experimental omics data continue to increase rapidly, there is great need of methods for proper model building and analysis which can handle this complexity.
In this project, we will focus on multi-scale modelling of biological systems, i.e. models which include different scales, from micro (e.g. models of metabolic networks) to macro (e.g. bioprocess models used in the context of the Process Analytical Technology (PAT) for screening, statistical monitoring and control). The project aims to tackle with the optimization of metabolites production by developing and applying new methods and tools for building, analyzing and applying multi-scale models under the realistic scenario of having uncertain data, typically either scarce highly informative or abundant yet low informative data
